In one embodiment, a method includes determining television content that a particular user is currently watching on a television and determining, using one or more sensors, an attention level for the particular user. The attention level indicates an amount of attention paid by the particular user to the television content. The method further includes generating an attention profile for the television content by aggregating the particular user's attention level for the television content with stored information associated with a plurality of other users about the television content. The attention profile indicates a number of users who paid attention to the television content. The method further includes determining digital content available on a social-networking system that is related to the television content and providing a comparison of the number of users who paid attention to the television content with engagement on the social-networking system with the related digital content.
Legal claims defining the scope of protection, as filed with the USPTO.
1. A system comprising: a television meter device comprising: one or more processors; a plurality of sensors; and one or more computer-readable non-transitory storage media communicatively coupled to the one or more processors, the media comprising instructions operable when executed by the one or more processors to cause the system to: determine television content that the particular user is currently watching on the television; and determine, using one or more of the sensors, a attention level for the particular user, the attention level indicating an amount of attention paid by the particular user to the television content; and one or more computer systems of a social-networking system, the one or more computer systems operable to: receive the particular user's attention level for the television content from the television meter device; generate an attention profile for the television content by aggregating the received particular user's attention level for the television content with stored information from other television meter devices about the television content, the attention profile indicating a number of users who paid attention to the television content; determine digital content available on the social-networking system that is related to the television content; and display a comparison of the number of users who paid attention to the television content with a number of users of the social-networking system who viewed the related digital content on the social-networking system.
2. The system of claim 1 , wherein the attention level determined by the television meter device is based at least on one or more of: a determination that eyes of the particular user are open for a predetermined amount of time; and a determination that a head pose of the particular user is towards the television.
3. The system of claim 1 , wherein the number of users of the social-networking system who viewed the related digital content on the social-networking system is determined by analyzing a social graph of the social-networking system to determine one or more of: a number of users of the social-networking system who shared or reacted to posts or stories associated with the related digital content; a number of users of the social-networking system who watched the related digital content on the social-networking system; and a number of users of the social-networking system who posted stories or comments about the related digital content.
4. The system of claim 1 , wherein: the television content comprises: a show; a movie; an advertisement; or an event; and the digital content available on the social-networking system that is related to the television content comprises: a story; a post; a video; or a comment.
5. The system of claim 1 , wherein the attention level determined by the television meter device is based at least on one or more of: a determination that the television is powered on; and a determination that the particular user is within a predetermined distance of the television.
6. The system of claim 1 , wherein the plurality of sensors comprises one or more of: a visible-light camera; an infrared (IR) camera; a motion sensor; and a microphone.
7. The system of claim 3 , wherein the social graph of the social-networking system comprises: a plurality of first nodes that are each associated with a respective user; a plurality of second nodes that are each associated with a respective show or movie; and a plurality of edges connecting the first nodes and the second nodes, each particular edge indicating that a particular user corresponding to a particular first node previously watched, reacted to, liked, shared, or commented on a particular show or movie corresponding to a particular second node.
8. A method, comprising: determining, by one or more computer systems, television content that a particular user is currently watching on a television; determining, by the one or more computer systems using one or more of a plurality of sensors, an attention level for the particular user, the attention level indicating an amount of attention paid by the particular user to the television content; generating, by the one or more computer systems, an attention profile for the television content by aggregating the particular user's attention level for the television content with stored information associated with a plurality of other users about the television content, the attention profile indicating a number of users who paid attention to the television content; determining, by the one or more computer systems, digital content available on a social-networking system that is related to the television content; and displaying, by the one or more computer systems, a comparison of the number of users who paid attention to the television content with a number of users of the social-networking system who viewed the related digital content on the social-networking system.
9. The method of claim 8 , wherein the attention level is based at least on one or more of: a determination that eyes of the particular user are open for a predetermined amount of time; and a determination that a head pose of the particular user is towards the television.
10. The method of claim 8 , wherein the number of users of the social-networking system who viewed the related digital content on the social-networking system is determined by analyzing a social graph of the social-networking system to determine one or more of: a number of users of the social-networking system who shared or reacted to posts or stories associated with the related digital content; a number of users of the social-networking system who watched the related digital content on the social-networking system; and a number of users of the social-networking system who posted stories or comments about the related digital content.
11. The method of claim 8 , wherein the television content comprises: a show; a movie; an advertisement; or an event.
12. The method of claim 8 , wherein the attention level is based at least on one or more of: a determination that the television is powered on; and a determination that the particular user is within a predetermined distance of the television.
13. The method of claim 8 , wherein the digital content available on the social-networking system that is related to the television content comprises: a story; a post; a video; or a comment.
14. The method of claim 8 , wherein the plurality of sensors comprises one or more of: a visible-light camera; an infrared (IR) camera; a motion sensor; and a microphone.
15. One or more computer-readable non-transitory storage media embodying software that is operable when executed to: determine television content that a particular user is currently watching on a television; determine, using one or more of a plurality of sensors, an attention level for the particular user, the attention level indicating an amount of attention paid by the particular user to the television content; generate an attention profile for the television content by aggregating the particular user's attention level for the television content with stored information associated with a plurality of other users about the television content, the attention profile indicating a number of users who paid attention to the television content; determine digital content available on a social-networking system that is related to the television content; and display a comparison of the number of users who paid attention to the television content with a number of users of the social-networking system who viewed the related digital content on the social-networking system.
16. The storage media of claim 15 , wherein the attention level is based at least on one or more of: a determination that eyes of the particular user are open for a predetermined amount of time; and a determination that a head pose of the particular user is towards the television.
17. The storage media of claim 15 , wherein the number of users of the social-networking system who viewed the related digital content on the social-networking system is determined by analyzing a social graph of the social-networking system to determine one or more of: a number of users of the social-networking system who shared or reacted to posts or stories associated with the related digital content; a number of users of the social-networking system who watched the related digital content on the social-networking system; and a number of users of the social-networking system who posted stories or comments about the related digital content.
18. The storage media of claim 15 , wherein the television content comprises: a show; a movie; an advertisement; or an event.
19. The storage media of claim 15 , wherein the attention level is based at least on one or more of: a determination that the television is powered on; and a determination that the particular user is within a predetermined distance of the television.
20. The storage media of claim 15 , wherein the digital content available on the social-networking system that is related to the television content comprises: a story; a post; a video; or a comment.
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October 10, 2017
September 24, 2019
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